Dynamically generating documents using natural language processing and dynamic user interface

ABSTRACT

An NLP analysis method based on identification of common terms is disclosed. The improved NLP analysis can separate different parts of a patent claim into discrete claim segments based on the common terms. A user interface that corresponds to a flowchart allows the user to drag and drop the claim segments to form complex relationships, which is used to generate a patent specification.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims the benefit of U.S.application Ser. No. 17/014,403, filed on Sep. 8, 2020, entitledDYNAMICALLY GENERATING DOCUMENTS USING NATURAL LANGUAGE PROCESSING ANDDYNAMIC USER INTERFACE, which is expressly incorporated by referenceherein in its entirety.

TECHNICAL FIELD

The present technology pertains to a method and apparatus for generatingdocuments using natural language processing and a dynamic userinterface.

BACKGROUND

Formal documents that are authored for administrative agencies arerequired to have specific structure to comport with the administrativeagency's requirements. The requirements include procedural-basedrequirements (e.g., margins, font size, etc.) and statutory-basedrequirements (content).

FIGS. 1 and 2 illustrate existing systems for generating patentapplications. In particular, FIG. 1 illustrates a server-based processto generate the formal document and FIG. 2 illustrates anapplication-based generation process to generate the patentspecification. In general, each of these systems generally receivesmethod claims as input and (1) converts the method claims into apparatusor device claims, (2) generates a description of a flowchart based on aset of method claims (i.e., a single independent claim and generally atleast one dependent claim that depends from that single independentclaim), and (3) creates a single generic flowchart diagram based on theindependent claim. The systems may also be able to insert generic devicedescriptions and boilerplate based on a client's requirements.

Referring to FIG. 1 , a system 100 comprises a client 110 that connectsto a webserver 120 for generating the patent specification. In thesystem 100, the client 110 transmits a document at step 135 thatincludes a set of method claims to the webserver 120. Having receivedthe document with method claims, the webserver 120 extracts the methodclaims from the document at step 140. After extracting the claim, thewebserver 120 transmits text that corresponds to the method claims tothe NLP server at step 145

The NLP server 130 receives the text and processes the text into NLPtokens at step 150. An NLP token (or token) is generally a single wordor a single character (e.g., punctuation) and is assigned severalproperties. For instance, each NLP token is generally assigned anidentifier (or ID), a part of speech tag that identifies the part ofspeech (e.g., noun, verb, etc.), and a dependency label that identifieshow the part of speech depends on other tokens, and so forth. Ingeneral, NLP engines also assign what is referred to as a fine part ofspeech, which further clarifies the purpose of that word. For example, anoun can be the object of the sentence, but could also be part of acompound noun (that is, a single object that has a name includingseveral words), which is also referred to as an n-gram.

A dependency label identifies how the token depends on other tokens. Forexample, an NLP token may be a determiner (i.e., an article such as“the” or “an”), a nominal subject, a clausal subject, an adverbialclause, conjunction, punctuation, and so forth. A dependency labelreferred to as root corresponds to the root of the sentence or phraseand is not dependent on any other tokens in that sentence. For example,in the sentence “I love fries,” the NLP token “love” is the root, “I” isthe proper noun having a dependency of noun subject from the root, and“fries” is the noun that is a direct object of the root. For example,the output of this sentence is illustrated in Table 1 below.

TABLE 1 Course Id RootId Text Tag Fine Tag Dependency Label 0 1 I NounPersonal Pronoun Nominal Subject 1 1 love Verb Non-3^(rd) person Rootpresent verb 2 1 fries Noun Plural Noun Direct Object

The NLP server 130 transmits the tokens to the webserver 120 at step155, which converts the tokens into a patent specification at step 160.The webserver 120 creates a flowchart and a corresponding description tothat flowchart based on NLP tokens from the method claims. To create thedescription of the flowchart, the webserver 120 extracts the individualportions of tokens that can be converted into a single sentence based onthe order in which they are identified in the method claim (i.e., text).

Specifically, the webserver 120 converts an active step, which is aclause having an active gerund as its root word, into a sentence using adifferent tense. For example, the webserver 120 may convert a phrase“performing a function” into “perform a function” and then add genericcontent such as “a processor may” to the beginning of the phrase, thusforming “a processor may perform a function.” In this case, the genericstructure is predetermined and not associated with user input. That is,the webserver 120 receives the method claims in a particular sequenceand then generates a flowchart description based on the order of claims.After generating the specification, the webserver 120 transmits thepatent specification with the flowchart description and additionalboilerplate back to the client 110 at step 165. The webserver 120 mayalso transmit any created flowchart drawings or generic drawings at step165.

FIG. 2 illustrates a system 200 that is similar to the system 100, buthas a different architecture. In particular, the system 200 comprises anapplication 210, which may be executing on a client computer, whichcommunicates with the NLP server 230.

The application 210 extracts the text of the method claims and transmitsthe text to the NLP server 230 at step 240. The NLP server 230 processesthe text into NLP tokens at step 250 and returns the text as NLP tokensat step 260 to the application 210. In response to receiving the NLPtokens, the application 210 may generate the specification or part ofthe specification at step 270. The application 210 generates a flowchartbased on the independent claim, generates a flowchart description basedon the order of the claims, and composes apparatus or device claims fromthe method claims.

As noted above, the system 100 or system 200 may also compose additionalclaims from the method claims. In more detail, the system 100 or system200 converts a method claim, which has gerund verbs, into a device orsystem claim, which has present tense verbs. However, in each case, thesystem 100 or system 200 will only provide generic structure (e.g., aprocessor, a memory, a display). The system 100 or system 200 may alsogenerate “means” claims by changing the preamble and adding “means for”before the root gerund verb.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIGS. 1 and 2 illustrate conventional systems for generating a patentspecification;

FIG. 3 illustrates a sequence diagram of an example system fordynamically generating documents using NLP and a dynamic user interface;

FIG. 4 is a flowchart of a method for segmenting text into tokens andclaim segments;

FIG. 5 is a flowchart of a method for sequencing claim segments togenerate a patent specification;

FIG. 6 illustrates an example user interface for arranging claimsegments to generate a patent specification and drawings;

FIG. 7 illustrates an example user interface for arranging claimsegments using a claim panel that simultaneously displays claim segmentsand claims based on a feedback scheme;

FIG. 8 illustrates an example node that allows complex manipulation ofclaim segments;

FIGS. 9A, 9B, and 9C illustrate an example node that allows complexrelationships of claim segments;

FIG. 10 illustrates a user interface that allows a user to build aspecification using point and click operations in conjunction with aclient-specific module;

FIG. 11 is a flowchart of a method for generating a patent specificationbased on a related application that is identified using NLP;

FIG. 12 illustrates an example user interface for generating aspecification based on a related application that is identified usingNLP; and

FIG. 13 illustrates an example computer system for executing client orserver operation.

DESCRIPTION

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.

As machine learning, especially natural language processing (NLP) becomemore robust it is tempting to look to these tools to perform certaintasks that are considered formulaic. While these tools are indeedbeneficial, they are not suitable for producing completed work productin most instances. Machine learning tools are not yet able to take rawinputs, understand them, and write an explanatory document about thoseraw inputs. Therefore previous attempts at document creation usingmachine learning tools have focused on using structured inputs.

In the example tools used for drafting patent applications, a commonstructured input has been claims. Indeed those skilled in the art ofdrafting patent applications often begin with claims because they arethe most important part of the document, and are designed to recite thenovel aspects of an invention. However, such tools are limited torestructuring clauses of claims into sentences and pasting them into adocument, which is insufficient to produce any useful work product.

For example, the existing tools only repeat the claims in the order theyare input via the document and do not distinguish between thedifferences in the claims. In a patent application, a dependent claimcould occur before the first limitation of an independent claim, couldoccur after the last limitation of the independent claim, or occuranywhere in between the first and last limitations. Moreover, adependent claim may add subject matter or may further define previousactions. For example, a passive phrase in a dependent claim furtherdefines subject matter to which it refers. Further, an active phrase maybe further defined by additional active phrases. The dependent claimsmay encompass multiple embodiments that are mutually exclusive (i.e.,different species).

Existing tools may only generate a drawing based on the independentmethod claim, thereby producing an incomplete drawing. Further, theexisting systems are also unable to identify condition-action sequences(e.g., if a condition is satisfied, perform a function) that would causethe flowchart to have branching logic because NLP itself is unable todisambiguate the meaning of phrases. The existing system are also unableto represent inherent conditions, thus omitting content in the drawingthat should be explicit.

The present technology improves over existing solutions by improving themachine-user interface, which provides further inputs into a naturallanguage processing server and yields a more robust output. For example,in some embodiments the present technology utilizes an input collectionof statements. In the case of a patent application the statements can beelements of claims, while in the case of a contract the statements canbe a description of major deal terms. In the case of a technical paperthese statements can be sentences reciting key points to be described.

The present technology can analyze the statements and can organize theminto an initial order based on relationships and dependencies perceivedbased on the tokens provided from the NLP server. This initialorganization can be in the form of a flowchart or an outline. Howeverthe present technology recognizes that, in the process of writing acomplex document, thoughts need to be rearranged, additional thoughtsmay be added, and thoughts may be refined. As such the presenttechnology provides an interface by which the initial order can bereorganized based on the judgment of a human author.

In some embodiments, the present technology can provide prompts to auser to provide disambiguation for terms, or to provide additionaldescriptive details. In this way, the present technology can encouragethe user to provide additional input that may be beneficial to the NLPanalysis.

By improving the machine-user interface, the present technology canultimately provide a more usable initial output to an author of adocument. A goal of the present technology is to provide the output thatprovides efficiency to an author, while leaving room for an author toprovide the ingenuity and thoughtfulness that only a human author canprovide.

Through improvements in the machine-user interface, the presenttechnology is also able to accommodate more complex relationshipsbetween phrases. For example the present technology can accommodate anddescribe conditional logic, or descriptions nested in otherdescriptions.

In addition the present technology provides various other improvements,some of which are specific to drafting of patent applications. Forexample the present technology encourages input of detailed and numerousdependent claims so that the NLP server can provide the foundation for adetailed patent application. However recognizing that there are somerestraints on the number of claims that an author may wish to include ina patent application, and recognizing that not all topics recited inclaim are useful for inclusion in a figure, the present technology canallow a user to suppress portions of a claim from appearing in a claimsection of a document or from appearing in the drawings accompanying apatent application.

These and other improvements to tools that use algorithms or NLP tocreate documents are described herein.

FIG. 3 illustrates a sequence diagram of an example system 300 fordynamically generating standardized documents using NLP and a dynamicuser interface. For example, the documents can be a document forsubmission to an administrative agency based on that administrativeagency's procedural requirements. The disclosed system can be applied toany type of standardized document that has a structure that may benefitfrom visually organizing concepts to form complex relationships frominput text.

In the context of a patent application, the system 300 provides animproved NLP analysis method that is illustrated in FIGS. 3 and 4 .Further, an application that is executing within the system 300 mayinclude a dynamic user interface that is illustrated in FIGS. 5 to 10 toallow the user to input method claims, sequence the steps of the claimstogether with an intuitive user interface, and intelligently composeportions of a patent specification. Further, the dynamic user interfaceallows the user to identify structures associated with actions withinthe claims, which can then be used to more intelligently compose claimsand draft the specification based on input method claims.

The system 300 comprises a client 302, a server 304, and a NLP server306. In some examples, the server 304 and the NLP server 306 can bedifferent server processes executing on the same hardware or configuredvirtual machine. In the event that the NLP server 306 is hosted locallyon the same server as the server 304, the NLP engine may be based on alocal NLP engine such as natural language toolkit (NLTK), StanfordCoreNLP, etc. However, the NLP server 306 may also be a third-partyserver such as Google Natural Language, Microsoft Cognitive Services, orAmazon Comprehend.

As an example, a virtual machine can execute a webserver in a reverseproxy configuration, which parses the requested uniform resourceidentifier (URI) and directs the request to the server 304 or NLP server306 based on the URI. For example, any URI beginning with “/nlp” (e.g.,“/nlp/document”, “/nlp/phrases”, etc.) is forwarded to the NLP serverexecuting on port 9000. Any other URI is forward to the server 304executing on port 6000. In another example, the functionality providedby the server 304 may be performed based on an application executing onthe client 302 (e.g., a Native React application, etc.) that includelocal libraries and is able to directly access the file system of theclient 302.

In this example, the client 302 receives an application from the server304 at step 308. For example, the application may be a component objectmodel (COM) plugin application that executes within another application(e.g., Microsoft Word®), a stand-alone application that nativelyexecutes as an application (e.g., a Windows® Presentation Foundation(WPF) application, etc.), or a hosted application that uses anotherapplication such as a web browser to render the user interface (e.g.,Native React, Electron JS, Blazor WebWindow, etc.). In some examples,the application can be web application (e.g., a Microsoft 365® add-in)that is side loaded into a local application (e.g., Microsoft Word) or aweb application (e.g., Microsoft 365®) and uses an API to performfunctions.

The client 302 may execute the application at step 310. As noted above,the application may be executed within a browser's sandbox. However, theapplication may also be an add-in and executes within anotherapplication such as a React-based add-in that is executed withinMicrosoft Word® and is able to use various APIs to interact with thedocument and the application. In the example illustrated in FIG. 3 , thesystem 300 is presumed to execute in a browser sandbox, and anydescriptions in FIG. 3 may be modified or changed based on the executionenvironment of the application.

At step 312, the application transmits the document including at leastone claim to the server. As noted above, FIG. 3 may be modified based onthe execution environment. As an example, if the application is a Reactadd-in that is executing within Microsoft Word, at step 312 theapplication may, using an API available via the application (Office.js,etc.), retrieve the text corresponding to the claims and transmit thetext to the NLP server 306.

After receiving the document, the server 304 extracts text from theclaims at step 314 and transmits text from the claims at step 316 to theNLP server 306. For example, the claim generally is separated by linebreaks and may include whitespace (e.g., spaces, tabs, line breaks,etc.) to illustrate relationships of subject matter in the claims. Themargins, indenting, and other paragraph properties can also be used toidentify relationships in the claims. Accordingly, identificationinformation of the claim is also extracted and transmitted to the NLPserver at step 316. For example, the identification information may bethe claim number and claim line encoded into a unique value, and thetext may be transmitted as a key-value pair at step 316. The NLP server306 processes the text into NLP tokens at step 318 and transmits thetokens and token identification information to the server at step 320.The NLP server 306 generates token identification information toindicate a position of the token in the input text and to identify tokenrelationships based on the various token properties (e.g., dependencylabel, part of speech, etc.).

At step 322, the server 304 generates token IDs, analyzes the NLPtokens, and creates new text at step 322. In particular, the server 304generates a token identifier for each token based on the identificationinformation and token identification information. Thus, the server 304generates a unique token identifier for each token based on the claimnumber of the token, the line number (based on the line breaks), and aposition of the token within that line. As will be described below, thetoken IDs generated by the server 304 allow supplemental NLP analysis ofdifferent segments to improve quality of the NLP.

The NLP analysis of the line of text may materially be affected based oncommon terms that are commonly used in patent claims. For example, theterm “wherein” may significantly affect the NLP analysis and cause theNLP to misidentify the root word. As noted above, the root word of aphrase or sentence is not dependent on any other tokens. Further, termssuch as “comprising” have specific legal definitions and may also affectthe quality of the NLP analysis. Thus, at step 322, the server mayanalyze the tokens and determine that a line of a claim should besegmented into different claim segments and then reanalyzed. The claimsegments are a consecutive list (i.e., an array) or NLP tokens that canbe converted into individual sentences by the system 300 and generallyform discrete concepts.

The claim segments are generally classified into an active phrase, apassive phrase, and a linking phrase. An active phrase includes a rootword that is a gerund verb. As an example, a segment that forms thephrase “transmitting information” comprises a token “transmitting” thathas a dependency label of root and a second “information” that has adependency label of clausal subject. In this example, because the system300 receives method claims, the root verbs will generally be gerundverbs. However, the system 300 could receive present tense verbs andsegment the claims in a substantially identical manner. In someexamples, there may be an adpositional phrase (e.g., “after receivingthe content,” “in response to receiving the content, etc.) that modifiesthe root verb. However, the core meaning of the segment stillcorresponds to the active gerund verb and the root token can be deducedbased on an analysis of the NLP tokens. The active phrase generallyincludes a direct object linked to the gerund verb and does not includea noun having a dependency label of nominal subject.

A passive phrase includes a subject that that further defines a conceptin another active phrase and generally includes both a nominal subjectand a clausal subject. In this case, the root word may be a presenttense or past tense verb. However, the verb can also be in active form.For example, a segment that forms the passive phrase “the informationincludes a power transmission level” comprises a root word of“includes,” which a present tense verb. However, “the information” is asingular noun that has a dependency label of nominal subject and “apower transmission level” is a clausal subject.

A linking phrase does not include content and provides context thatlinks two claim segments. As an example, the linking phrase “theprocessing of the data comprises” further indicates that content afterthe linking phrase is linked to and modifies “processing the data.”

Accordingly, the server 304 creates portions of text by excluding someof the common terms that affect the NLP analysis and transmits theportion of text to the NLP server 306 at step 324. The text transmittedat step 324 may also include identifying information to facilitatesynthesis of the NLP tokens. At step 326, the NLP server 306 processesthe text into NLP tokens and transmits a second set of tokens to theserver 304 with the identification information at step 328. Theidentification information transmitted to the NLP server 306 at step 324may be different than identification information transmitted at step316. For example, text transmitted at step 324 may be in the form of akey-value pair with the key corresponding to the token ID of the firsttoken in the text.

At step 330, using the identification information, the server 304synthesizes the first set of tokens and the second set of tokens into acomplete set of tokens in step 320. The complete set of tokenscorresponds to the entirety of the claim and includes the common terms.With the NLP tokens synthesized, the server 304 transmits the completeset of tokens to the client 302 (i.e., the application executing on theclient 302) at step 332.

The client application, which will be further described below withrespect to FIG. 5 , allows the NLP tokens to be rearranged in aflowchart user interface based on user input. However, in some cases,the steps that should be illustrated in a flowchart are not necessarilyexplicit in a claim. For example, if a claim is a condition-actionsequence (e.g., if something exists, perform a function), the claimimplicitly recites two actions: the determining of the condition and theaction that is performed based on the condition. Therefore, in somecases, it is beneficial to allow a user to input additional actions thatshould be incorporated into a flowchart and its correspondingdescription.

Accordingly, to allow the user to add additional content (i.e., nodes)to the flowchart user interface, the application may allow the user toinput additional language. That is, the application enables the user toinput supplemental text that is separate from the text of the claims atstep 334. In response, the application executing on the client 302 maytransmit the supplemental text to the server 304 at step 336. The server304 transmits the text to the NLP server 306 at step 338. In this case,the server does not provide identifying information because the server304 will not necessarily need to resynthesize the NLP tokens. The NLPserver 306 processes the text into NLP tokens at step 340 and transmitsthe tokens to the server at step 342. The server 304 transmits thetokens to the client 302 at step 344.

At step 346, the client 302 selects at least one template that is usedto configure a patent specification. However, step 346 is onlyillustrated as an example and can occur prior to claim analysis andtokenization described above or at other stages of the presenttechnology. In response to the user's selection of at least one templateat step 346, the client 302 transmits a request for the template to theserver 304 at step 348. The server 304 replies with the at least onetemplate at step 350. The template includes static information that maybe updated based on the user's manipulation of the client application.For example, a template can include standard boilerplate, a blankdrawing that is inserted to be a placeholder, a flowchart descriptionstyle, a client specific drawing that is relevant to many of thatparticular client's patent applications, and so forth.

In some examples, the template may insert the content into multiplesections of the patent specification. As an example, a template that isrelated to blank diagram that serves as a placeholder (i.e., forpreserving of reference numbers and other labels) may only insert ablank description into a drawing description section and a descriptionsection. However, a client specific system overview may includedifferent regions related to background, technical field, summary, anddescription. Further, the templates may include a corresponding sectionthat identifies entities associated with the claims. As will bedescribed in further detail below, the entities may be hardwarecomponents that the user can link to via a claim segment, which may alsobe used to compose new claims based on the method claims input into thesystem 300.

At step 352, the user operates the application on the client 302 togenerate specification data. As an example, a flowchart user interfaceis presented to the user and allows the user to organize claim segmentsin a manner that will be used to visually describe the flowchart, whichwill be further described below with respect to FIGS. 6 to 10 . Further,as noted above with respect to step 346, the user is able to selectdifferent templates, perform client specific functions, and so forth togenerate the specification data. The specification data may includedifferent data structures that are used to generate the specificationdocument and may include, for example, user authored claims, applicationcomposed claims, a list of templates and data associated with thetemplates, flowchart data for generating descriptions of the flowchart,descriptions of the flowchart, static data (e.g., docket number,inventor names, client information, etc.) and so forth.

The specification data 354 is transmitted to the server 304 at step 354because, in this example, the client application is executing within thebrowser sandbox and is unable to access system resources. Accordingly,the server 304 receives the specification data, generates a documentbased on the specification data, and generates drawings based on thespecification data. The server 304 then transmits the document anddrawing to the client 302 at step 358. In other examples, theapplication may be executing within document processing application(i.e., Microsoft Word®, Libre Office, etc.) and may generate thedocument on the client 302 itself using an API.

In the example illustrated in FIG. 3 , an improved NLP analysis methodis described that identifies common terms that causes NLP errors. Byfurther segmenting the text based on the common terms and performing asubsequent NLP analysis, the quality of the NLP analysis is improved andthe NLP tokens can be easily dissected into different claim segmentsthat will form complete sentences in the generated patent specification.

Although the above and below disclosure relates to a patent application,the disclosure can also be applicable to content that relates to asequence of operations. For instance, the disclosure can be applied to aflow diagram illustrating communication between devices, softwareprocesses, services, or any other type of communication. The instantdisclosure can also be applied to legal and/or formal documents foridentifying a sequence, an order, a succession, conditional logic,decision trees, and so forth.

FIG. 4 illustrates an example method 400 for segmenting the text intoNLP tokens and claim segments that are used by a client application forcreating a patent specification. The descriptions below relate toaspects that can be integral to a user application or separate from theuser application (e.g., implemented on a server). For the sake ofclarity, the method 400 is described separately from other aspects thatrelate to the machine-user interface. Although the example method 400depicts a particular sequence of operations, the sequence may be alteredwithout departing from the scope of the present disclosure. For example,some of the operations depicted may be performed in parallel or in adifferent sequence that does not materially affect the function of themethod 400. In other examples, different components of an example deviceor system that implements the method 400 may perform functions atsubstantially the same time or in a specific sequence.

According to some examples, the method 400 includes transmitting textassociated with patent claims to a server for NLP analysis at step 402.For example, the processor 1305 illustrated in FIG. 13 may transmit textassociated with patent claims to a server for NLP analysis. In thisexample, the patent claims comprise an independent claim and at leastone dependent claim that form a set of claims. While it is possible touse a single independent claim, a set of claims generally includes atleast one dependent claim.

According to some examples, the method 400 includes receiving NLP tokensfrom the server based on the NLP analysis at step 404. For example, theprocessor 1305 illustrated in FIG. 13 may receive NLP tokens from theserver based on the NLP analysis.

According to some examples, the method 400 includes generating a tokenidentifier for each NLP token at step 406. For example, the processor1305 illustrated in FIG. 13 may generate a token identifier for each NLPtoken. In an example, the token identifier includes a claim number, aline number, and a token number within the line. In particular, theclaim number, line number, and token number are each encoded into thetoken identifier using different base numbers or Gödel numbering. Thetoken number within the line indicates an order of the token within theline.

According to some examples, the method 400 includes identifying commonterms in the NLP tokens that affect the NLP analysis at step 408. Forexample, the processor 1305 illustrated in FIG. 13 may identify commonterms in the NLP tokens that affect the NLP analysis. In an example, thecommon terms comprise at least one of comprising, comprises, and aphrase to indicate a definition. In another example, the common termscomprises patent terms having a legal definition or provide a contextfor a claim segment and further explain the content of the claim.

According to some examples, the method 400 includes, in response toidentifying the common terms, generating segments of text based on thecommon terms and transmitting the segments of text to the server for asecond NLP analysis at step 410. For example, the processor 1305illustrated in FIG. 13 may, in response to identifying the common terms,generate segments of text based on the common terms and transmit thesegments of text to the server for a second NLP analysis.

According to some examples, the method 400 includes receiving a secondset of NLP tokens from the server based on the second NLP analysis atstep 412. For example, the processor 1305 illustrated in FIG. 13 mayreceive a second set of NLP tokens from the server based on the secondNLP analysis.

According to some examples, the method 400 includes synthesizing the NLPtokens and the second set of NLP tokens into a complete set of NLPtokens corresponding to the text associated with the patent claims atstep 414. For example, the processor 1305 illustrated in FIG. 13 maysynthesize the NLP tokens and the second set of NLP tokens into acomplete set of NLP tokens corresponding to the text associated with thepatent claims. In an example, the passive phrase includes a presenttense verb and a nominal subject. In another example, the active phrasescomprise a gerund verb that corresponds to a root word of the claimsegment based on the NLP analysis. In another example, the passivephrase further defines a gerund verb or an object in another claimsegment. In a fourth example, the generating of the claim segmentscomprises identifying content that links different claims andidentifying linking phrases that link different claim segments. In afifth example, each claim segment corresponds to an active phrase or apassive phrase. In a sixth example, the complete set of NLP tokensincludes claim segments, each claim segment comprising a plurality ofNLP tokens. In a seventh example, the common terms are excluded from anyof the claim segments.

In another example, the synthesizing of the tokens at step 414 comprisesidentifying a relationship between different claim segments based on thelinking phrases. For example, the processor 1305 illustrated in FIG. 13may identify a relationship between different claim segments based onthe linking phrases. A linking phrase does not include content, butsimply provides context that links two segments. For example, a preambleof a claim may include “the processing of the data comprises,” whichfurther indicates that content after preamble is a linked to andmodifies “processing the data.”

According to some examples, the method 400 includes extractingwhitespace for each line of the patent claims at step 416. For example,the processor 1305 illustrated in FIG. 13 may extract whitespace foreach line of the patent claims. Based on procedural requirements, aclaim is required to be a single sentence, but a claim is generallybroken into individual lines using a line break to provide structure tothe claim and separate different clauses. Whitespace includes spaces,tabs, line breaks that may be used to provide visual formatting to theclaim. In terms of document file formats, the underlying text may beseparated into several different XML elements and whitespace may berepresented by properties of the XML, elements. As an example, aparagraph element is represented in OpenXML (i.e., a word .docx file) asa <w:p> element with the “w” identifying the namespace and the “p”identifying a paragraph element. The paragraph element can include childXML elements such as a paragraph properties element (i.e., a <w:pPr>element) that provides whitespace such as, the indent of the first line,the left margin, a tab element, a hanging indent, etc.

According to some examples, the method 400 includes identifyingrelationships between the claim segments based on the whitespace, aclaim number associated with the claim segment, and a claim dependencyat step 418. For example, the processor 1305 illustrated in FIG. 13 mayidentify relationships between the claim segments based on thewhitespace, a claim number associated with the claim segment, and aclaim dependency. Further, claim lines (or recitations) may includewhitespace to further indicate that the recitation is related to theprior subject matter in the claim.

According to some examples, the method 400 includes determining an orderof a portion of the claim segments based on the relationships of theclaim segments, the order corresponding to an order of a flowchart thatis presented to a user, at step 420. For example, the processor 1305illustrated in FIG. 13 may determine an order of a portion of the claimsegments based on the relationships of the claim segments, the ordercorresponding to an order of a flowchart that is presented to a user.

In an example, the user provides input into the flowchart to generate aportion of the specification data. According to some examples, themethod 400 includes receiving supplemental text that is input separatelyfrom the claims at step 422. For example, the processor 1305 illustratedin FIG. 13 may receive supplemental text that is input separately fromthe claims. For example, the user may enter text into a component tocreate a user-defined segment for the flowchart user interface asdescribed below.

According to some examples, the method 400 includes transmitting thesupplemental text to the server at step 424. For example, the processor1305 illustrated in FIG. 13 may transmit the supplemental text to theserver.

According to some examples, the method 400 includes receiving a thirdset of NLP tokens from the server corresponding to the supplemental textat step 426. For example, the processor 1305 illustrated in FIG. 13 mayreceive a third set of NLP tokens from the server corresponding to thesupplemental text.

According to some examples, the method 400 includes receivingspecification data generated based on user manipulation of the claimsegments at step 428. For example, the processor 1305 illustrated inFIG. 13 may receive specification data generated based on usermanipulation of the claim segments. The specification data is generatedbased on user input into a client application to rearrange the initialordering of the claim limitations that were originally determined basedon the NLP analysis and logical analysis described above. A methodassociated with the creating the specification data is illustrated inFIG. 5 and examples of the user interface and corresponding features areillustrated in FIGS. 6 to 10 and further described below.

In an example, the specification data comprises flowchart data that isgenerated at the client application based on user manipulation. In someexamples, the specification data identifies a list of templates and datarelated to the templates (e.g., Figure number) as illustrated in FIGS.10 and 12 . The specification data includes different data that isgenerated by the client 302 and is used by the server 304 to generatethe specification.

According to some examples, the method 400 includes generating a patentspecification that comports with a plurality of procedural requirementsbased on the specification data at step 430. For example, the processor1305 illustrated in FIG. 13 may generate a patent specification thatcomports with a plurality of procedural requirements based on thespecification data. The patent specification can also include a set ofdrawings.

In an example, the generating of the specification at step 430 mayinclude determining that the specification data includes custom contentfor a first template in a list of templates. For example, the processor1305 illustrated in FIG. 13 may determine that the specification dataincludes custom content for a first template in the list of templates.In another example, the generating of the specification at step 430further comprises extracting first content from a document correspondingto the first template.

In another example, the generating of the specification at step 430comprises generating text in a description section of the patentspecification based on at least one claim. For example, the processor1305 illustrated in FIG. 13 may generate text in a description sectionof the patent specification based on at least one claim. The descriptionin this case corresponds to the flowchart description of a drawing andspecifically links the description to the flowchart with a referencenumeral.

Further, the generating the specification at step 430 further includesdetermining whether the specification data indicates that a claimsegment is linked to a structure that performs an action correspondingto the claim segment. After determining a claim segment is linked, themethod further includes generating text corresponding to the claimsegment that indicates that the structure performing the action of theclaim segment. For example, the processor 1305 illustrated in FIG. 13may determine whether the specification data indicates that a claimsegment is linked to a structure that performs an action correspondingto the claim segment and may generate text in the flowchart descriptionthat indicates the structure performing the action of the claim segment.The action of the text has a different verb tense than the action in theclaim segment and the text includes a reference numeral of the structurethat identifies the structure in a drawing. Thus, as illustrated inFIGS. 6 and 7 , the specification is generated based on a user inputinto the user interfaces (e.g., the control 652 in FIG. 6 ) that links ahardware diagram to a claim segment in the flowchart user interface. Inparticular, when generating the description related to the flowchart,the description identifies the step in the flowchart and providesexplicit support to a hardware structure that also performs this step.

The generating the specification at step 430 further includessynthesizing the first content and the custom content into mergedcontent for inserting the merged content into the generated patentspecification. For example, the processor 1305 illustrated in FIG. 13may synthesize the first content and the custom content into mergedcontent. For instance, based on previous input identifying a specificstructure in the client application, the corresponding action in theflowchart user interface can be inserted into text associated with thehardware. That is, the link used in the control, which is illustrated ascontrol 652 in FIG. 6 , can simultaneously generate text for a flowchartand text associated with the hardware figure. For example, if atransmitter X10 is selected to perform “transmitting power levelinformation,” the description associated with the transmitter X10 can bemodified to indicate that the transmitter X10 transmits the power levelinformation. As noted above, this input can also be used to modify thedescriptions of the flowchart, thereby allowing a single user interfaceto change different content in different sections of the patentspecification.

However, in some embodiments, processor 1305 can receive an input thatwill indicate at that at least one claim from the input claims should beexcluded from a claim section of the patent specification. This resultsin a claim being be used to generate text for the description, but isexpressly excluded from the claims in the specification generated atstep 430. This can be a beneficial feature whereby an input claim setcan articulate all concepts that a user desires to be processed by NLPserver 130 and included in the patent document, while focusing the claimset with the most useful claims in the claim set.

In another example, the generating of the patent specification at step430 comprises generating a preliminary amendment based on thespecification data. For example, the processor 1305 illustrated in FIG.13 may generate a preliminary amendment based on the specification data.Similar to the second example, additional claims can be used generatethe specification, but can be removed via preliminary amendment toprevent incurring excess claim fees.

According to some examples, the method 400 includes transmitting thepatent specification to a client application that generates thespecification data at step 432. Further, the method 400 can alsotransmit a set of drawings to the client. For example, the processor1305 illustrated in FIG. 13 may transmit the patent specification to aclient application that generates the specification data. In some cases,the method 400 may be executing locally on a client machine and theclient machine would therefore create the document or insert the contentof the patent specification into an existing document that is open in aword processing application.

While the above discloses improves NLP analysis, despite the generalproficiency of the NLP server in understanding language structure, theNLP server is not always able to arrange claim segments in an optimalorder for explaining an invention embodied in claims. In some instances,these limitations of the NLP server are rooted in the formal structureof claims, and that an aim of the drafters is for the claims to be onlyminimally descriptive of an invention (e.g., claims are intended todefine a minimum novelty to result in a patentable claim that providesthe broadest rights to which the applicant is entitled). In view of boththese technological limitations and the limitations of the inputprovided to the NLP server, the present technology provides an interfaceto receive inputs to rearrange the initial ordering of the claimlimitations that were originally determined by NLP server and to includesupplemental text in addition to the language in the input claims.

FIG. 5 illustrates an example method 500 for sequencing claim segmentsto generate a patent specification using examples of various aspects ofa dynamic user interface illustrated in FIGS. 6 to 10 . For purposes ofclarity, the descriptions below relate to a client application that isexecuting and outputting a flowchart user interface to allow the user tovisually draft the patent specification.

Although the example method 500 depicts a particular sequence ofoperations, the sequence may be altered without departing from the scopeof the present disclosure. For example, some of the operations depictedmay be performed in parallel or in a different sequence that does notmaterially affect the function of the method 500. In other examples,different components of an example device or system that implements themethod 500 may perform functions at substantially the same time or in aspecific sequence.

According to some examples, the method includes receiving NLP tokensfrom an NLP analysis of patent claims at step 502. For example, theprocessor 1305 illustrated in FIG. 13 may receive NLP tokens from an NLPanalysis of patent claims. In an example, the patent claims comprise anindependent claim and at least one dependent claim that form a set ofclaims.

According to some examples, the method 500 includes generating claimsegments from the NLP tokens at step 504. For example, the processor1305 illustrated in FIG. 13 may generate claim segments from the NLPtokens. In another example, each claim segment corresponds to an activephrase or a passive phrase. The passive phrase further defines a gerundverb or an object in another claim segment. In another example, theactive phrase comprises a gerund verb that corresponds to a root word ofthe claim segment based on the NLP analysis.

According to some examples, the method 500 includes selecting a portionof claim segments to display at step 506. For example, the processor1305 illustrated in FIG. 13 may select a portion of claim segments todisplay.

According to some examples, the method 500 includes displaying aflowchart including the portion of the claim segments arranged in afirst order at step 508. For example, the processor 1305 illustrated inFIG. 13 may display a flowchart including the portion of the claimsegments in the first order. An example of a flowchart displaying anorder of claim segments is illustrated in FIGS. 6 and 7 .

In another example, the method 500 comprises displaying a claim areathat illustrates the set of claims and claim segments corresponding tothe set of claims. For example, the processor 1305 illustrated in FIG.13 may display a claim area 702. An example claim area 702 is depictedin FIG. 7 and provides visual feedback to facilitate user operation.

According to some examples, the method 500 includes receiving an inputto change the first order of the claim segments into a second order thatis different from the first order at step 510. For example, theprocessor 1305 illustrated in FIG. 13 may receive an input to change thefirst order of the claim segments into the second order that isdifferent from the first order. As further described below withreference to FIGS. 6, 7, 8, 9A, 9B, and 9C, the user interface allowsthe user to drag and drop claim segments in the flowchart to formcomplex relationships. The user input can also be other operations suchas a click operation that in a conditional branch that identifies theorder of claim segments.

In an example, the input comprises dragging the second claim segmentinto the flowchart, and, after the second claim segment is dragged intothe flowchart, a first graphical demarcation is applied to the secondclaim segment in the claim area. In another example, the input comprisesdragging the third claim segment into the flowchart, and, after thethird claim segment is dragged into the flowchart, the first graphicaldemarcation is applied to the third claim segment in the claim area.

The demarcations is the flowchart user interface provide visualinformation regarding a state of the claim segment. This visualinformation allows the user to understand the organization of theflowchart to understand how the flowchart itself will be used to draftthe patent specification.

For example, FIG. 7 illustrates a first graphical demarcation (indicatedby the border) applied to claim segments 706, 708, and 714 and indicatesthat each claim segment is displayed in the flowchart user interface(i.e., the executing application and not the patent application orcorresponding drawings). In another example, FIG. 7 illustrates a secondgraphical demarcation applied to a claim segment 704 in the claim areaindicates that the claim segment 704 comprises active language and isnot displayed in the flowchart. In another example, FIG. 7 illustrates athird graphical demarcation applied to claim segments 710 and 716 in theclaim area indicates that each segment comprises passive language and isnot displayed in the flowchart.

According to some examples, the method 500 includes displaying the claimsegments in the flowchart in the second order at step 512. For example,after receiving an input effective to indicate a rearrangement of theclaim segments, the processor 1305 illustrated in FIG. 13 may displaythe claim segments in the flowchart in the second order.

According to some examples, the method 500 includes receiving an inputto link another drawing with the current flowchart at step 514. Forexample, the processor 1305 illustrated in FIG. 13 may receive an inputto link another drawing with the current flowchart. For example, FIG. 6below illustrates a control 654 that allows selection of another drawingwhich will permit cross reference between the flow chart and the anotherdrawing when the patent specification is later created.

According to some examples, in response to the input at step 514, themethod 500 includes identifying a structure in the linked drawing. Forexample, the processor 1305 illustrated in FIG. 13 may identify astructure in the linked drawing. For instance, a template fileassociated with the drawing may identify a plurality of structures thatare selectable in the user interface.

According to some examples, the method 500 includes updating controlsassociated with the claim segments at step 518. For example, theprocessor 1305 illustrated in FIG. 13 may update controls associatedwith the claim segments. In an example, the structures identified in thetemplate file may populate the controls located in the nodes to allowselecting of a structure that performs the action corresponding to theclaim segment.

According to some examples, the method 500 includes receiving an inputin a control associated with a claim segment at step 520. For example,the processor 1305 illustrated in FIG. 13 may receive an input in acontrol associated with a claim segment. In response to receiving theinput, the claim segment corresponding to the control is then associatedwith performing the action. Accordingly, when the text of the patentspecification is generated based on the specification data, the textwill explicitly link the action associated with the claim segment withthe structure. For example, FIG. 6 illustrates controls 652 that allowslinking a structure to a claim segment that a user can select differentstructures based on the drawing selected in control 654.

According to some examples, the method 500 includes receiving a secondinput to indicate that language of a second claim segment partiallydefines a first claim segment that is displayed within the flowchart atstep 522. For example, the processor 1305 illustrated in FIG. 13 mayreceive a second input to indicate that the language of a second claimsegment partially defines a first claim segment that is displayed withinthe flowchart. For example, as described below, FIG. 8 illustrates thatclaim segment 812 and claim segment 814 can be dragged into a node 800to further define claim segment 802 of the node 800.

According to some examples, the method 500 includes displaying a firstsub-flowchart within the first claim segment in the flowchart at step524. For example, the processor 1305 illustrated in FIG. 13 may displaya first sub-flowchart within the first claim segment in the flowchart.In an example, a first drawing is generated from the specification datathat corresponds to the flowchart and a second drawing is generated fromthe specification data that corresponds to the first sub-flowchart. Inthis first example, the first sub-flowchart further defines the actionassociated with the first claim segment. For example, FIG. 8 illustratesa sub-flowchart that further defines claim segment 802.

According to some examples, the method 500 includes receiving a thirdinput to indicate that the language of a third claim segment partiallydefines the first claim segment displayed within the flowchart at step526. For example, the processor 1305 illustrated in FIG. 13 may receivea third input to indicate that the language of a third claim segmentpartially defines the first claim segment displayed within theflowchart.

According to some examples, the method 500 includes displaying a secondsub-flowchart within the first claim segment in the flowchart at step528. For example, the processor 1305 illustrated in FIG. 13 may displaya second sub-flowchart within the first claim segment in the flowchart.In an example, a first drawing is generated from the specification datathat corresponds to the flowchart, a second drawing is generated fromthe specification data that corresponds to the first sub-flowchart, anda third drawing is generated from the specification data thatcorresponds to the second sub-flowchart. In this example, the secondsub-flowchart also further defines the action associated with the firstclaim segment. Thus, the first sub-flowchart and the secondsub-flowchart may be different species and may be mutually exclusive andmultiple drawings may be generated based on the input into the flowchartuser interface. As an example, FIG. 8 illustrates a tabbed interface forallowing different sub-flowcharts to be associated with a single claimsegment 802.

According to some examples, the method includes receiving an input toselect at least one claim from the set of claims at step 530. Forexample, the processor 1305 illustrated in FIG. 13 may receive an inputto select at least one claim from the set of claims. In an example, atleast one claim is excluded from a claim section of the patentspecification. As noted above, this results in a claim being be used togenerate text for the description, but is expressly excluded from theclaims in the specification.

According to some examples, the method 500 includes determining whetheran identifier for the patent specification corresponds to a first entityat step 532. For example, the processor 1305 illustrated in FIG. 13 maydetermine whether an identifier for the patent specification correspondsto a first entity. As will be described below with reference to FIG. 10, the identifier is used to execute a client-specific module 1014 toperform common events that are particular to that client. For example, afirst client may require multiple timing diagrams, a second client mayrequire a circuit diagram having a similar layout, and a third clientmay require an engine illustration that requires different labels.

According to some examples, the method 500 includes, when the identifiercorresponds to the first entity, executing a module exclusivelyassociated with the first entity at step 534. For example, the processor1305 illustrated in FIG. 13 may, when the identifier corresponds to thefirst entity, execute a module exclusively associated with the firstentity.

According to some examples, the method 500 includes, in response to userinput into the module, generating client specific data based on themodule. For example, the processor 1305 illustrated in FIG. 13 may, inresponse to user input into the module, generate a portion of thespecification data based on the module, the portion of the specificationdata be used to generate a drawing specific to the first entity. In oneexample, the client specific data is used to generate a drawing and acorresponding description specific to the first entity at step 536.

According to some examples, the method 500 includes generatingspecification data used to create a patent specification. The patentspecification includes a description of the flowchart based on thesecond order at step 538. Further, the specification data may includethe client specific data generated at step 536. For example, theprocessor 1305 illustrated in FIG. 13 may generate specification dataused to create a patent specification, the patent specificationincluding a description of the flowchart based on the second order. Thespecification data includes all data necessary for generating aspecification. For instance, the specification data may identify atleast one template that is used to generate a description and drawings.The specification data may also include text generated at the clientapplication that can be injected into the at least one template. Asnoted above, the drawing may include a flowchart and at least onesub-flowchart that further defines nodes within the flowchart. Inanother example, multiple flowcharts may be generated based on using abypass node, which is described below in connection with FIGS. 9A to 9C.

In an example, the generating of the specification data comprisescomposing a device claim based on the independent claim. In anotherexample, the device claim includes the text indicating that thestructure performs the action corresponding to the first claim segment.In another example, the specification data includes data related to apreliminary amendment that is created to cancel at least one claim fromthe set of claims. In another example, the specification data comprisessettings data related to options for controlling the generation of thepatent specification. For example, the settings data may comprise anyvariation of the specification such as using “Figure” in lieu of “FIG,”or any other stylistic preference. For example, the setting data mayinclude a flag indicating two spaces between sentences. In general, thesettings data is generally based on preferences. However, the settingsdata may also include content related to generating the variousdescriptions of the flowcharts. For instance, the flowchart may bedescribed in a breadth first or a depth first manner. In other examples,the settings data initially set in the application based on anothertemplate file that forms the underlying document for a particular clientand includes data such as header text for the various headers in thespecification, fonts, styles, margins, etc. As noted above, thespecification data is used by an application or a server to generate aspecification and drawings.

In addition, the method 500 may include additional steps not explicitlyidentified above. For instance, the method 500 may include identifying afirst occurrence of a noun object (i.e., an n-gram) within the claimsegments based on the order of the claim segments. In this case, themethod 500 may insert language to indicate to the user to add additionaldescription regarding this term.

FIG. 6 illustrates an example user interface 600 for arranging claimsegments to generate a patent specification and drawings. In thisexample, the application is executing in the browser environment.However, the application could be a stand-alone application thatnatively executes in the operating system or an application add-in(e.g., a Microsoft Word® add-in).

As illustrated in FIG. 6 , the rendered view from the browser displaysthe user interface 600 that corresponds to a flowchart user interface.The user interface comprises a grid having a plurality of nodes (i.e.,processes and other operations within the flowchart) and edges (i.e.,arrows) between the nodes to illustrate a flowchart. In particular, node602, node 604, node 606, node 608, node 610, and node 612 are displayedin the grid. Although not illustrated, the user interface 600 mayinclude start and end nodes.

Each node illustrated in FIG. 6 is associated with at least one claimsegment. Specifically, claim segment 614 is displayed via node 602,claim segment 616 is displayed via node 604, claim segment 618 isdisplayed via node 606, claim segment 620 is displayed via node 608,claim segment 622 is displayed via node 610, and claim segment 624 isdisplayed via segment 612. In this example, the nodes serve as visualcontainers for the claim segments, enable complex user inputs, and allowcomplex associations of the claim segments to be simultaneously formedand displayed.

Each node displayed in FIG. 6 is associated with at least one drop zonefor receiving a claim segment as an input and change an order of theflowchart illustrated in the user interface 600. In general, each nodeincludes a drop zone below the node and a drop zone adjacent to thenode. Specifically, node 602 is associated with drop zone 626 and dropzone 628, node 604 is associated with drop zone 630 and drop zone 632,node 606 is associated with drop zone 634 and drop zone 636, node 608 isassociated with drop zone 638 and 640, node 610 is associated with dropzone 642 and drop zone 644, and node 612 is associated with drop zone646 and 648.

The drop zones simultaneously provide a visual order to the flowchartand also enable dragging and dropping of segments to reorder theflowchart. As an example, drop zone 626 and drop zone 628 are associatedwith node 602. The drop zone 628 is sequentially links the node 602 tonode 604 by virtue of the arrow (i.e., edge) located within the dropzone 628. However, dropping another claim segment into drop zone 628informs the application that the dropped segment is should be positionedbetween nodes 602 and 604. Thus, the drop zones allow a claim segment tobe dragged and dropped into the corresponding drop zone, which insertsthe claim segment at the corresponding location and allows the user tomanipulate the claim segments to visually construct a flowchart usingclaim segments.

FIG. 6 illustrates claim segment 618 as a node preceding claim segment620. FIG. 6 also illustrates that claim segment 622 is displayed as abranch of claim segment 618. This branch is the result of claim userinterface 600 receiving a drag and drop of segment 622 into drop zone634. Thus, at claim segment 618, the method illustrated in the userinterface 600 can proceed to either claim segment 620 or claim segment622. As illustrated in FIG. 6 , after this drop event, the userinterface 600 has created an additional column in the user interface 600for displaying the claim segment 622. After this drop event hasoccurred, a drop event could still be received in drop zone 634 toposition another claim segment between claim segment 618 and claimsegment 622. Similarly, a claim segment can be received into drop zone636 to cause the claim segment to be positioned between claim segment618 and claim segment 620.

The user interface 600 also allows the complex display of the variousclaim segments. For example, a passive claim segment 650 may bedisplayed within node 602 to visually illustrate that the passive claimsegment 650 further defines subject matter within claim segment 614. Toposition the passive claim segment 650, claim segment 650 is dragged anddropped into claim segment 614. However, as will be described below withreference to FIG. 8 , dropping an active claim segment into claimsegment 614 will create an embedded sub-flowchart within the node 602.

The node 602 may also illustrate a control 652 for selecting a devicethat performs the action in claim segment 614. The user interface 600also includes a control 654 that allows a corresponding figure to beselected. Using the control 654, the user is able to select the figure(e.g., Figure A in this example) that includes a list of structures(e.g., XX 210 selected in control 652, XX220 selected in node 606, etc.)that can populate the control 652. By selecting the control 652, theclaim segment 614 can be linked to structures in different drawings inconnection with generating the patent specification.

That is, the user interface 600 displays a flowchart user interface thatallows the user to intuitively drag and drop various claim segments in asimple manner. As such, the user is able to quickly and accurately orderthe claim segments, which also changes the underlying data structure andaffects how the description of the flowchart will be written by theapplication. In addition, the control 652 and control 654 allow the userto select a hardware figure and corresponding structure, which will beused to generate the specification. In other examples, by selecting thestructure via the control 652 and control 654, a claim can be composedto include that the selected structures perform the correspondingaction.

Nodes within conditional branches may also include an additional controlfor identifying a return node and creating a return arrow 658 thatillustrates the flow of the method. In FIG. 6 , node 622 is the finalnode of the branch and therefore includes a return control 656 toindicate the next node within another branch. In FIG. 6 , the node 622has been changed to return the flow of the illustrated method to labelX60 corresponding to node 612.

FIG. 7 illustrates an example illustration of a user interface 700 forarranging claim segments and includes a claim panel 702 that displaysclaim segments embedded within the claims based on a feedback scheme.

In particular, FIG. 7 illustrates three claims (A, B, and C). Claim Aincludes claim segment 704, claim segment 706, claim segment 708, andclaim segment 710. In addition, claim A incudes a common word 712 thatis not allocated to any claim segments and any trailing or leadingpunctuation or whitespace is excluded from the claim segments. Claim Bincludes claim segment 714 and claim C includes claim segment 716.

The user interface 700 allows the user to drag a claim segment from theclaim panel 702 and drop a claim segment as described above withreference to FIG. 6 . In particular, claim segment 714 was previouslydragged to precede claim segment 706 in the flowchart user interface.Although not illustrated, claim segment 704 is not displayed because itprecedes claim segment 714 within user interface 700 and can be viewedby scrolling. For clarity, the dashed lines illustrated in FIG. 7illustrate claim segment 706, claim segment 708, and claim segment 714and their respective positions in the user interface 700 and the claimpanel 702. The claim segment 706, claim segment 708, and claim segment714 may also include a label (e.g., a reference numeral) that is used tolabel each active claim segment in the user interface 700 and the claimpanel 702. For instance, claim segment 706 is labeled with YY3 and claimsegment 714 is labeled with YY1.

Claim segment 718, which precedes claim segment 714 in the userinterface 700, is not illustrated in the claim panel 702 and may eitherbe provided from another claim that is not illustrated in claim panel702 or may be separately input using, for example, a supplementalsegment component for allowing the user to manually create claimsegments. Similarly, claim segment 720 and claim segment 722 are notillustrated in the claim panel 702 and may be associated with claims notillustrated in claim panel 702 (i.e., the claims can be viewed if theclaim panel 702 is scrolled downward) or may be separately input and arenot found within the claims.

Further, the claim segments illustrated in the claim panel 702 may becolor coded to provide visual feedback. In the example illustrated inFIG. 7 , when a claim segment is allocated (i.e., assigned a position)within the user interface 700, the claim segment may be coded with afirst color. In particular, claim segment 704, claim segment 706, claimsegment 708, and claim segment 714 are allocated within the userinterface 700 (with claim segment 704 not being viewable based onscrolling the user interface 700). As noted throughout this disclosure,the various claim segments can be added, moved, and removed from theflowchart. When a corresponding claim segment is deleted from theflowchart (using the delete icon), the claim segment is referred to asunallocated.

Claim segment 710 and claim segment 716, which are displayed in theclaim panel 702, are not allocated and are color coded to provideadditional feedback. In particular, claim segment 710 is coded with asecond color to indicate that claim segment 710 is an active phrase andis not allocated within the user interface 700. Claim segment 716 iscoded with a third color to indicate that claim segment 716 is a passivephrase and is also not within the user interface 700. Claim segment 710and claim segment 716 also do not include a reference label because theyare not allocated within the user interface 700.

Although not illustrated in FIG. 7 , the claim segments (or nodes thatprovide visual containers for the claim segments) may include a deleteicon that allows the claim segment to be unallocated from the userinterface 700. In response to input to delete a claim segment, the userinterface 700 would recalculate the flowchart illustrated in the userinterface 700 and change the feedback provided by the correspondingclaim segment in the claim panel 702.

In addition, the nodes may each contain a grouping option that allowsnodes to be combined into groups or combined with a previous paragraphwhen the specification is drafted. In this example, a grouping option724 for claim segment 720 and a grouping option 726 are illustrated andremaining nodes are not illustrated with this option for convenience.When the grouping options 724 and 726 are selected, the specificationgeneration groups these claim segments and drafts the specificationbased on the grouping. That is, the claim segments 720 and 722 may bedescribed in a single paragraph for simplicity.

Further, the claim segments in the user interface 700 may be configuredto be excluded from the final set of claims. In an example, thereference label in the claim segment 722 may be selected to indicatethat this subject matter can be excluded from the final claims. In thisexample, when the reference label is selected, the reference label isreplaced by an option 728 that is unchecked to indicate that the claimassociated with the claim segment 722 is to be omitted from the finalclaims. When the option 728 is further selected, the claim correspondingto the claim segment 722 would be included. The option 728 may also beused to suppress a node from being created in a corresponding aflowchart drawing (i.e., a drawing document including the flowchart).

Thus, the claim panel 702 provides a visual feedback scheme that is usedin conjunction with the user interface 700 to allow the user to easilymanipulate the various claim segments to visually draft thespecification using a drag and drop user interface. In addition,additional user interface options are illustrated that further allowfiner control of the specification and allowing the user to includecontent generated from the input claims while simultaneously excludingthese claims from the finalized claims. As a result, the user is able toprovide a detailed set of preliminary claims to effectively draft allnecessary details, then selectively remove claims from the claimssection in the generated patent specification.

In another example, a separate component can be provided to allow claimsto be composed into different statutory classes using the claim segmentsand various templates. In such a component, the user would be able toselect a final set of claims based on the set of preliminary claims andthe composed claims. The application could manage the claim contentusing the user interface to ensure correct claim numbering, correctclaim dependency, and so forth.

FIG. 8 illustrates an example node 800 that allow complex manipulationof claim segments to create complex descriptions in the patentspecification. In particular, the node 800 can be associated with claimsegment 802, which has been allocated reference label YY1 and includes adelete icon 804 and a control 806 for selecting a structure to performthe action associated with claim segment 802. Further, the node 800 caninclude a tab interface 810 to allow other active claim segments thatfurther define claim segment 802. In the example illustrated in FIG. 8 ,claim segment 812 and claim segment 814 further define a firstembodiment illustrated in the first tab 816. That is, a claim segment812 further defines claim segment 802 by recited an action that isencompassed within claim segment 802.

Further, the first embodiment illustrated in tab 816 can include dropzone 818, drop zone 820, drop zone 822, drop zone 824, and drop zone 826to allow other claim segments to be dropped into the first tab 816.Thus, the node 800 may contain a separate sub-flowchart interface fullyembedded within a claim segment. Moreover, each segment within the nodecan also include a separate flowchart interface, allowing unlimitedrecursion of flowcharts.

The tab interface 810 can also include multiple tabs such as second tab828 and third tab 830 in this example. To generate the first tab, theclaim segment 812 is dragged and dropped into the claim segment 802 (ornode 800). Similarly, to generate the second tab, another segment (notshown) is dragged into the claim segment 802 (or node 800).

The second tab 828 and third tab 830 allow different claim segments tobe inserted, thereby allowing multiple embodiments that are mutuallyexclusive to be provided. Moreover, when generating the specification,the different embodiments illustrated in the first tab 816, second tab828, and third tab 830 will be described separately in the patentspecification, thereby allowing the system to generate a more accuratespecification and require less human editing and revision.

FIGS. 9A, 9B, and 9C illustrate an example node 900 that allowsdifferent alternatives. In particular, FIGS. 9A, 9B, and 9C illustrate abypass segment that allows optional actions to be defined in the userinterface.

Specifically, FIG. 9A, the node 900 includes a tab interface including afirst tab 902, second tab 904, and a third tab 906 for illustrationpurposes. The first tab 902 comprises an arrow 908 that corresponds toan edge in graph theory and simply indicates that no further actionsoccur at node 900. That is, in the first tab 902, the node 900 isbypassed in the execution of the flowchart.

However, if the user selects the second tab 904, the node 900 displaysthe second tab 904 illustrated in FIG. 9B. In FIG. 9B, the second tab904 is associated with a claim segment 910, and indicates an optionalnode that can be executed in the flowchart.

Further, if the user selects the third tab 906, the node displays thethird tab 906 illustrated in FIG. 9C. The third tab comprises aflowchart user interface 912 that is embedded and allows additionalclaim segments to be inserted and manipulated based on dragging anddropping into the claim segments and drop zones as noted above.

That is, in the example illustrated in FIGS. 9A, 9B, and 9C, theapplication may be configured to generate different flowcharts using thebypass segment in node 900. The application may also be configured togenerate sub-flowcharts linked to the main flowchart similar to FIG. 8 .

The examples illustrated in FIGS. 8, 9A, 9B, and 9C illustrate that thenodes allow optional segments and optional sub-flowcharts to be definedto thereby allow more complex associations with the claim segments to bedefined. Based on the various nodes described above, the user interfaceis able to represent an entire set of method claims regardless of thecomplexity of the method claims. However, while the various examples canbe illustrated in a single dynamic user interface, generating a singledrawing with all detail may not be possible. Accordingly, in someexamples, the system may also generate a separate drawing for eachsub-flowchart or may generate additional flowcharts illustrating allvariations of the flowcharts.

Further, the above examples illustrate simple flowcharts for clarity andconciseness. However, the user interfaces illustrated above can beembedded into nodes, thereby allowing unlimited complexity if required.Further, at best one conditional branch is illustrated, but conditionscan be linked (i.e., a switch operation) to allow unlimited complexityin the flowchart. For simplicity, the above user interfaces are referredto as directed acrylic graph (DAG) because the flow of the userinterface does not allow a previous node to be revisited. However, theinstant disclosure is not limited to DAG and can be bidirectional,allowing previous nodes to be revisited (i.e., a loop).

FIG. 10 illustrates a user interface 1000 that allows a user to provideinput into the user interface 1000 to build a specification using pointand click operations in conjunction with a client-specific module. Inparticular, the user interface 1000 illustrates a header region 1002, atemplate region 1004, and a specification region 1006. The header region1002 is related to a “wizard” or “stepper” component that allows theuser to select different stages to control the creation of the patentspecification. As will be described below, the header region 1002dynamically adds and removes steps based on inputs received ininterfaces prior to the presentation of user interface 1000, inputsafter the presentation of user interface 1000, and inputs into the userinterface 1000.

In the user interface 1000, the user selects different templates thatare used to generate the specification from the template region 1004. Inresponse, the specification region 1006 generates a specificationsection corresponding to a template selected in the template region 1004and provides some detail, such as the illustrated figure number (e.g.,Figure A). Although the specification sections illustrated in thespecification region 1006 generally are associated with illustrations,the specification sections can also include text-only regions such as aboilerplate related to a legal interpretation of a term. As an example,the text-only region can include text that is devised based on theadministrative agency's guidance with respect to a particular legalissue (e.g., subject matter eligibility) or administrative issue thatcomports with the agency's guidance.

Further, the different specification sections can easily be rearrangedin the specification region 1006 to allow the user to essentially pointand click to create a specification.

In FIG. 10 , the example user interface includes a specificationtemplate 1008 related to a first method claim (claim A) and aspecification template 1010 related to a second claim (claim C). Theuser is able to select either specification template 1008 and/orspecification template 1010, which then allows the user interface 1000to add a module 1012 corresponding to that claim. As illustrated in FIG.10 , the user selects the specification template 1008, which causes theheader region 1002 to dynamically insert a module 1012 for generatingcontent associated with that claim. As noted above, the module may be aflowchart user interface. Further, as illustrated in FIG. 10 , claim Bis not detected as a method claim and, therefore, the template region1004 excludes any potential drawing related to a flowchart for claim B.However, in some examples, the system may generate a flowchart based ona device or system claim using NLP.

FIG. 10 also illustrates a client-specific module 1014, which was addedbased on an identification of the client. In this example, the client isa legal entity (e.g., a corporation) or a person that would benefit fromthe operation of a module 1014 that is specific to their needs. That is,the application determines whether the patent specification to begenerated corresponds to a specific client that has a client module forgenerating specification data. If the patent specification correspondsto the specific client, the client-specific module 1014 is inserted intothe component for execution before or after the user interface 1000.

The client-specific module 1014 provides a user interface to creatingspecification data that is specific to that client. A client may havespecific content that needs to be recreated and the client-specificmodule 1014 provides a user interface for generating the same. Forexample, a first client may require multiple timing diagrams, a secondclient may require a circuit diagram having a similar layout, and athird client may require an engine illustration that requires differentlabels. Using the NLP tokens, claim segments, inputs described above,and other inputs unique to the client-specific module 1014, theclient-specific module 1014 may generate specification data for creatinga drawing and specification content. Thus, the client-specific module1014 is tuned specifically for each client to provide better and moreaccurate specifications.

FIG. 11 illustrates a flowchart of a method 1100 for generating aspecification based on related application that is identified using NLP.Although the example method 1100 depicts a particular sequence ofoperations, the sequence may be altered without departing from the scopeof the present disclosure. For example, some of the operations depictedmay be performed in parallel or in a different sequence that does notmaterially affect the function of the method 1100. In other examples,different components of an example device or system that implements themethod 1100 may perform functions at substantially the same time or in aspecific sequence.

According to some examples, the method 1100 includes transmitting textassociated with patent claims to a server for NLP analysis, the patentclaims comprising an independent claim and at least one dependent claimthat form a set of claims at step 1102. For example, the processor 1305illustrated in FIG. 13 may transmit text associated with patent claimsto a server for NLP analysis, the patent claims comprising anindependent claim and at least one dependent claim that form a set ofclaims.

According to some examples, the method 1100 includes receiving NLPtokens from the server based on the NLP analysis and a list of objectsthat are identified in the text based on the NLP analysis at step 1104.For example, the processor 1305 illustrated in FIG. 13 may receive NLPtokens from the server based on the NLP analysis and a list of objectsthat are identified in the text based on the NLP analysis. In this case,the list of objects are n-grams (i.e., compound words) that areextracted from the claims.

According to some examples, the method 1100 includes identifying genericlabels in the list of objects that distinguish similar objects from eachother at step 1106. For example, the processor 1305 illustrated in FIG.13 may identify generic labels in the list of objects that distinguishsimilar objects from each other. For example, the generic label may bean ordinal number (first, second, etc.), a past tense adjectivalmodifier (e.g., selected, displayed, etc.), and so forth.

According to some examples, the method 1100 includes, for each similarobject, removing the generic labels to create a single objectcorresponding to each similar object at step 1108. For example, theprocessor 1305 illustrated in FIG. 13 may, for each similar object,remove the generic labels to create a single object corresponding toeach similar object.

According to some examples, the method 1100 includes generating a termfrequency (TF) for a set of first objects based on the list of objectsat step 1110. For example, the processor 1305 illustrated in FIG. 13 maygenerate a term frequency (TF) for a set of first objects based on thelist of objects. That is, the generic label is stripped from the n-gramto distill the n-grams to their most basic form and count the mostfrequent n-grams.

According to some examples, the method 1100 includes searching a patentapplication repository based on the TF of the set of first objects atstep 1112. For example, the processor 1305 illustrated in FIG. 13 maysearch a patent application repository based on the TF of the set offirst objects. In an example, the searching of the patent applicationrepository is based on a comparison of claims.

In an example of the searching at step 1112, the method 1100 comprisescomparing the TF of the set of first objects with a second list ofobjects, the second list of objects being associated with a secondpatent application in the patent application repository and beinggenerated based on a TF of objects identified by claims in the secondpatent application. For example, the processor 1305 illustrated in FIG.13 may compare the TF of the set of first objects with a second list ofobjects, the second list of objects be associated with a second patentapplication in the patent application repository and be generated basedon a TF of objects identified by claims in the second patentapplication.

Further, searching at step 1112 may comprise determining whether toinclude the second patent application in the list of patent applicationsbased on the comparison of the TF of the set of first objects and thesecond list of objects. For example, the processor 1305 illustrated inFIG. 13 may determine whether to include the second patent applicationin the list of patent applications based on the comparison of the TF ofthe set of first objects and the second list of objects.

In another example, the searching at step 1112 may comprise receiving atleast one additional search parameter that is input by a user. Forexample, the processor 1305 illustrated in FIG. 13 may receive at leastone additional search parameter that is input by a user. In an example,the searching of the patent application repository is further based onthe at least one additional search parameter.

In the second example, the searching at step 1112 may further comprisecomparing the TF of the set of first objects with a third list ofobjects, associated with a second patent application, the third list ofobjects being generated based on an term frequency-inverse documentfrequency (TF-IDF). For example, the processor 1305 illustrated in FIG.13 may compare the TF of the set of first objects with a third list ofobjects, associated with a second patent application, the third list ofobjects be generated based on an TF-IDF. In an example, the determiningof whether to include the second patent application in the list ofpatent applications is further based on the comparison of the TF of theset of first objects and the TF-IDF. Because the specification may havea high frequency of common generic structures, it may be preferable togenerate the TF-IDF for the second patent application, thereby allowinga better comparison of claims to the specification.

According to some examples, the method 1100 includes receiving a list ofpatent applications corresponding to the TF based on the search of thepatent application repository at step 1114. For example, the processor1305 illustrated in FIG. 13 may receive a list of patent applicationscorresponding to the TF based on the search of the patent applicationrepository.

According to some examples, the method 1100 includes receivingspecification data generated based on user manipulation of a pluralityof claim segments associated with the NLP tokens, the specification dataincluding selection data related to a first patent application, at step1116. For example, the processor 1305 illustrated in FIG. 13 may receivespecification data generated based on user manipulation of claimsegments as described above with reference to FIG. 5 . However, in thisexample, the specification data also may include selection data relatedto another patent application, which is selectively incorporated basedon user input.

According to some examples, the method 1100 includes identifying adocument associated with the first patent application and extractingspecification content from the document based on the selection data atstep 1118. For example, the processor 1305 illustrated in FIG. 13 mayidentify a document associated with the first patent application andextract specification content from the document based on the selectiondata.

In another example, the identifying at step 1118 comprises identifying astart of first content related to a figure number identified by theselection data. For example, the processor 1305 illustrated in FIG. 13may identify a start of first content related to a figure numberidentified by the selection data.

Further, the identifying at step 1118 further comprises identifying astart of second content related to a second figure number that followsthe figure number identified by the selection data. For example, theprocessor 1305 illustrated in FIG. 13 may identify a start of secondcontent related to a second figure number that follows the figure numberidentified by the selection data.

Further, the identifying at step 1118 comprises extracting thespecification content that is located between the first content and thesecond content. For example, the processor 1305 illustrated in FIG. 13may extract the specification content that is located between the firstcontent and the second content.

Further, the identifying at step 1118 comprises searching referencenumerals in the specification content based on an original figure numberassigned to drawing content in the first patent application. Forexample, the processor 1305 illustrated in FIG. 13 may search referencenumerals in the specification content based on an original figure numberassigned to draw content in the first patent application.

Further, the identifying at step 1118 comprises replacing the referencenumerals based on the figure number assigned to the specificationcontent. For example, the processor 1305 illustrated in FIG. 13 mayreplace the reference numerals based on the figure number assigned tothe specification content.

Further, the identifying at step 1118 comprises identifying a summarydescription corresponding to the figure number in a section of the firstpatent application related to drawing descriptions. For example, theprocessor 1305 illustrated in FIG. 13 may identify a summary descriptioncorresponding to the figure number in a section of the first patentapplication related to drawing descriptions.

Further, the identifying at step 1118 comprises extracting the summarydescription. For example, the processor 1305 illustrated in FIG. 13 mayextract the summary description.

According to some examples, the method 1100 includes editing thespecification content based on a figure number assigned to thespecification content at step 1120. For example, the processor 1305illustrated in FIG. 13 may edit the specification content based on afigure number assigned to the specification content.

According to some examples, the method 1100 includes generating a patentspecification based on the specification data and including thespecification content, the patent specification comporting with aplurality of procedural requirements, at step 1122. For example, theprocessor 1305 illustrated in FIG. 13 may generate a patentspecification based on the specification data and include thespecification content, the patent specification comport with a pluralityof procedural requirements.

According to some examples, the method 1100 includes identifying adrawing associated with the first patent application and extractingdrawing content from the drawing based on the selection data at step1124. For example, the processor 1305 illustrated in FIG. 13 mayidentify a drawing associated with the first patent application andextract drawing content from the drawing based on the selection data.However, the disclosure can also be applicable to content that relatesto content reuse through searching using different techniques. Forinstance, the disclosure can be applied to a legal document (e.g., acontract, an agreement, etc.) and/or a formal document (e.g., apetition, a plan, a proposal, a request for proposal (RFP), changerequest, invoice, etc.) comporting with at least one procedure, statute,or requirement.

According to some examples, the method 1100 includes editing the drawingcontent based on the figure number at step 1126. For example, theprocessor 1305 illustrated in FIG. 13 may edit the drawing content basedon the figure number.

In another example, the editing of the drawing content at step 1126comprises searching text labels based on an original figure numberassigned to the drawing content in the first patent application. Forexample, the processor 1305 illustrated in FIG. 13 may search textlabels based on an original figure number assigned to the drawingcontent in the first patent application.

Further, the method 1100 comprises replacing a portion of the textlabels based on the figure number assigned to the specification content.For example, the processor 1305 illustrated in FIG. 13 may replace aportion of the text labels based on the figure number assigned to thespecification content.

According to some examples, the editing of the drawing content at step1126 comprises generating patent drawings based on the specificationdata and including the drawing content at step 1128. For example, theprocessor 1305 illustrated in FIG. 13 may generate patent drawings basedon the specification data and include the drawing content.

FIG. 12 illustrates an example user interface 1200 that may implement aportion of the features described in FIG. 11 . FIG. 12 illustrates a“wizard” or “stepper” component similar to FIG. 10 including a header1202 and a specification region 1206. The user interface 1200 furtherincludes a search results panel 1208 that illustrates a firstapplication 1210, a second application 1212, and a third application1214, which are identified based on a result of the TF search describedabove.

Each application displayed in the search results panel 1208 includesvarious static information such as serial number, docket number, asummary, and a description. The description may be scrollable or mayallow the user to selectively display a portion of the description.Using the user interface for each application, the user is able toquickly review each drawing and may identify related content that issimilar to the current application that is being drafted.

Similar to FIG. 10 , the user interface 1200 allows the user to select adrawing and selectively incorporate the same into the specificationregion 1206. As illustrated in FIG. 12 , with respect to FIG. 11 , thesystem generates specification data identifying the subject matter fromthe first application 1210 and second application 1212 to incorporate inthe current application. Because current documents and drawings arestored in an XML format, the system is able to extract the selectedcontent from the original source, modify the selected content based onthe user input, and insert the modified content. However, in someexamples, the drawing may not be stored in an XML format. In that case,the system may convert the drawing into a bitmap and then insert thebitmap drawing into the new drawing.

The examples disclosed above allow more accurate and more completepatent specifications to be generated using a dynamic and intuitive userinterface. Further, the examples disclosed above allow bettertokenization of the claims. Further, unlike existing system, because thedisclosed user interface can represent all method claims and variationsof the method claims, complex specifications and more complex drawingscan be created, which minimizes revision of the generated patentspecification. In addition, prior systems have only contemplatedgenerating a single flowchart for each set of method claims. However,the examples described above disclose that a set of method claims can beconverted into multiple flowcharts and multiple descriptions. The patentspecifications generated by the instant disclosure therefore are morecomplete, more accurate, and require minimal revision, thereby providinga benefit over existing systems. Finally, a search system is disclosedthat searches for related applications using NLP analysis of the claimsand NLP analysis of the previously filed patent application. Using thedisclosed search system, the user is able to selectively incorporatecontent from related applications and the search system updates theselected content to facilitate editing and incorporating additional ordifferent subject matter.

FIG. 13 illustrates an example computer system 1300 for executing clientor server operations. For example, the example computer system 1300 mayexecute a client application, a server side application for performingthe instant disclosure, or an NLP engine.

The example computer system 1300 includes a processor 1305, a memory1310, a graphical device 1315, a network device 1320, interface 1325,and a storage device 1330 that communicate and operate via a connection1335. The connection 1335 can be a physical connection via a bus, or adirect connection into processor 1305, such as in a chipsetarchitecture. The connection 1335 can also be a virtual connection,networked connection, or logical connection.

The processor 1305 reads machine instructions (e.g., reduced instructionset (RISC), complex instruction set (CISC), etc.) that are loaded intothe memory 1310 via a bootstrapping process and executes an operatingsystem for executing applications within frameworks provided by theoperating system. That is, the processor 1305 can include anygeneral-purpose processor and a hardware service or software service,which are stored in memory 1310, and configured to control processor1305 as well as a special-purpose processor where software instructionsare incorporated into the actual processor design. The processor 1305may essentially be a completely self-contained computing system,containing multiple cores or processors, a bus, memory controller,cache, etc. A multi-core processor may be symmetric or asymmetric.

For example, the processor 1305 may execute an application that executesan application provided by a graphical framework such as Winform, WPF,Windows User Interface (WinUI), or a cross platform user interface suchas Xamarin or QT. In other examples, the processor 1305 may execute anapplication that is written for a sandbox environment such as a webbrowser.

The processor 1305 controls the memory 1310 to store instructions, userdata, operating system content, and other content that cannot be storedwithin the processor 1305 internally (e.g., within the various caches).The processor 1305 may also control a graphical device 1315 (e.g., agraphical processor) that outputs graphical content to a display 1340.In some example, the graphical device 1315 may be integral within theprocessor 1305. In yet another example, the display 1340 may be integralwith the computer system 1300 (e.g., a laptop, a tablet, a phone, etc.).In some example, the graphical device 1315 may be integral with theprocessor 1305 and form an accelerated processing unit (APU).

The graphical device 1315 may be optimized to perform floating pointoperations such as graphical computations, and may be configured toexecute other operations in place of the processor 1305. For example,controlled by instructions to perform mathematical operations optimizedfor floating point math. For example, the processor 1305 may allocateinstructions to the graphical device 1315 for operations that areoptimized for the graphical device 1315. For instance, the graphicaldevice 1315 may execute operations related to artificial intelligence(AI), natural language processing (NLP), and vector math. The resultsmay be returned to the processor 1305. In another example, theapplication executing in the processor 1305 may provide instructions tocause the processor 1305 to request the graphical device 1315 to performthe operations. In other examples, the graphical device 1315 may returnthe processing results to another computer system (i.e., distributedcomputing).

The processor 1305 may also control a network device 1320 for transmitsand receives data using a plurality of wireless channels 1345 and atleast one communication standard (e.g., Wi-Fi (i.e., 802.11ax, 802.11e,etc.), Bluetooth®, various standards provided by the 3rd GenerationPartnership Project (e.g., 3G, 4G, 5G), or a satellite communicationnetwork (e.g., Starlink®). The network device 1320 may wirelesslyconnect to a network 1350 to connect to servers 1355 or other serviceproviders. The network device 1320 may also be connected to the network1350 via a physical (i.e., circuit) connection. The network device 1320may also directly connect to local electronic device 1360 using apoint-to-point (P2P) or a short range radio connection.

The processor 1305 may also control an interface 1325 that connects withan external device 1370 for bidirectional or unidirectionalcommunication. The interface 1325 is any suitable interface that forms acircuit connection and can be implemented by any suitable interface(e.g., universal serial bus (USB), Thunderbolt, and so forth). Theexternal device 1365 is able to receive data from the interface 1325 toprocess the data or perform functions for different applicationsexecuting in the processor 1305. For example, the external device 1365may be another display device, a musical instrument, a computerinterface device (e.g., a keyboard, a mouse, etc.), an audio device(e.g., an analog-to-digital converter (ADC), a digital-to-analogconverter (DAC)), a storage device for storing content, anauthentication device, an external network interface (e.g., a 5Ghotspot), a printer, and so forth.

The storage device 1330 can be a non-volatile memory device and can be ahard disk or other types of computer readable media which can store datathat are accessible by a computer, such as flash memory, solid statememory devices, an electro-mechanical data storage such as a hard diskdrive (HDD), optical storage medium such as digital versatile disks,cartridges, random access memories (RAMs), read only memory (ROM),and/or some combination of these devices. In some embodiments thecomputer-readable storage devices, mediums, and memories can include acable or wireless signal containing a bit stream and the like. However,when mentioned, non-transitory computer-readable storage media expresslyexclude media such as energy, carrier signals, electromagnetic waves,and signals per se.

The storage device 1330 can include software services, servers,services, etc., that when the code that defines such software isexecuted by the processor 1305, it causes the system to perform afunction. In some embodiments, a hardware service that performs aparticular function can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as processor 1305, connection 1335, external device1370, etc., to carry out the function.

While much of the above description is focused on receiving claimsegments as an input into the natural language processing engine, otherinputs are possible. For example, in some embodiments, an initial inputcould be a figure having labels. In such an embodiment, the draftingsystem would identify each label and query an author for a descriptionof the labeled portion and its interaction or relationship with anotherlabeled portion. These descriptions of the labeled portions and theirinteractions or relationships with other labeled portions can be fedinto the natural language processing server. Thereafter the naturallanguage processing server can output structured statements in aninitial sequence for additional refinement and rearranging by the useras described above.

While much of the above description referred to the presentation ofclaim segments in the form of a flowchart other mechanisms for thepresentation of the claim segments (structured statements) arecontemplated. For example a flowchart can be viewed as a stand-in for anoutline. A flowchart as discussed above as an example embodiment mainlybecause it is also a required feature of a software patent application,but an outline format would be just as effective. And in outline formatwould be more intuitive for other types of documents. In an outlineformat individual statements can be levels of an outline, and just asdescribed above the various levels of outline can be rearranged intoindependent concepts and nested concepts just as described above.

As described above the present technology can receive any collection ofstatements having a basic relationship between the statements and canextract parts of speech from these statements and provide an initialorganization for the statements. Thereafter the present technology canreceive further inputs to rearrange and modify and add to the statementsand ultimately provide an initial draft of a document. In this way thepresent technology provides advantages over existing technologiesthrough improvements in the machine-user interface improvements andinputs to natural language processing server improvements income termsof complexity of initial inputs and subsequent inputs which all canresult in a better initial draft provided by the national languageprocessing server and available from existing technologies.

The disclosed system can be applied to any type of standardized documentthat has a structure that may benefit from visually organizing conceptsto form complex relationships from input text. In some examples, thedisclosed system can be used to arrange a contract or an agreement basedon text input. In other examples, the disclosed system can be used a newdrug application at the FDA, a change request for a manufacturingprocess, a non-disclosure agreement, a technical paper that presents aflowchart or sequence diagram.

The disclosed system can be used to arrange a contract or another typeagreement based on text input (e.g., a non-disclosure agreement, anemployment agreement, a contract, etc.). An agreement related to acontract may need to specify obligations and consequences of achievingof failing to achieve those obligations. The instant disclosure couldreceive a text-based input and generate a flowchart, which would then beconverted into legal text based on various templates.

In other examples, the disclosed system can be used a new drugapplication at the U.S. Food & Drug Administration (FDA), a changerequest for a manufacturing process, or a proposal. As an example, thedisclosed system may implement a named entity recognition (NER) moduleto identify chemical compounds and use the identified chemical compoundsto create a user interface that would allow the user to controlcomponents to create description for the new drug application.

Additional concepts can be incorporated to further benefit the disclosedsystem. For instance, an NER module can be trained based on patentclaims to identify common words and identify points to segment claimsand identify logical breaks in claims. An NER module may also be used toanalyze language and generate a sequence diagram illustratingcommunication between different devices such as FIG. 3 of the instantdisclosure. The user would be provided an interface similar to thedisclosure above to allow correction of the communication sequence andthen further create a description of the communication sequence.

However, the disclosure can also be applicable to content that relatesto content reuse through searching using different techniques. Forinstance, the disclosure can be applied to a legal document (e.g., acontract, an agreement, etc.) and/or a formal document (e.g., apetition, a plan, a proposal, a request for proposal (RFP), changerequest, invoice, etc.) comporting with at least one procedure, statute,or requirement.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

Any of the steps, operations, functions, or processes described hereinmay be performed or implemented by a combination of hardware andsoftware services or services, alone or in combination with otherdevices. In some embodiments, a service can be software that resides inmemory of a client device and/or one or more servers and perform one ormore functions when a processor executes the software associated withthe service. In some embodiments, a service is a program, or acollection of programs that carry out a specific function. In someembodiments, a service can be considered a server. The memory can be anon-transitory computer-readable medium.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although the example method illustrated herein depict a particularsequence of operations, the sequence may be altered without departingfrom the scope of the present disclosure. For example, some of theoperations depicted may be performed in parallel or in a different. Inother examples, different components of an example device or system thatimplements the methods illustrated herein may perform functions atsubstantially the same time or in a specific sequence.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims. Moreover, claimlanguage reciting “at least one of” a set indicates that one member ofthe set or multiple members of the set satisfy the claim.

What is claimed is:
 1. A method for generating a document, comprising:receiving text comprising at least one independent claim; analyzing thetext using a natural language processor (NLP) to generate NLP tokensfrom the text; identifying at least a portion of the NLP tokens for asubsequent analysis; analyzing additional text corresponding to theportion of the NLP tokens to generate second NLP tokens; merging thesecond NLP tokens into the NLP tokens; and generating a patentspecification, the patent specification including a description of aflowchart that is generated based on the NLP tokens.
 2. The method ofclaim 1, further comprising: generating a unique identifier associatedwith at least a portion of the text, wherein merging the second NLPtokens into the NLP tokens is based on the unique identifier.
 3. Themethod of claim 2, wherein the unique identifier includes at least oneof a claim number, a line identifier, and a token position on associatedwith the line identifier.
 4. The method of claim 1, further comprising:analyzing whitespace associated with the text to form a relationshipbetween at least two lines of text separated by a line break, whereinthe patent specification is generated based on the relationship of theat least two lines.
 5. The method of claim 1, wherein the portion of theNLP tokens comprises a phrase that modifies a root object associatedwith a line of the text.
 6. The method of claim 1, further comprising:generating claim segments for the at least one independent claim fromthe NLP tokens based on an analysis of the NLP tokens.
 7. The method ofclaim 6, further comprising: displaying information corresponding to theclaim segments.
 8. The method of claim 7, wherein a claim segment of theclaims segments is linked to a structure that is associated with the atleast one independent claim.
 9. The method of claim 8, wherein thepatent specification includes at least one sentence including thestructure and text generated based on the claim segment.
 10. The methodof claim 1, further comprising: displaying a user interface forinteracting with the at least one of the text and the NLP tokens,wherein the patent specification is generated based on interactionswithin the user interface.
 11. A non-transitory computer readable mediumcomprising instructions, the instructions, when executed by a computingsystem, cause the computing system to: receive text comprising at leastone independent claim; analyze the text using a natural languageprocessor (NLP) to generate NLP tokens from the text; identify at leasta portion of the NLP tokens for a subsequent analysis; analyzeadditional text corresponding to the portion of the NLP tokens togenerate second NLP tokens; merge the second NLP tokens into the NLPtokens; and generate a patent specification, the patent specificationincluding a description of a flowchart that is generated based on theNLP tokens.
 12. The computer readable medium of claim 11, wherein thecomputer readable medium further comprises instructions that, whenexecuted by the computing system, cause the computing system to:generate a unique identifier associated with at least a portion of thetext, wherein merging the second NLP tokens into the NLP tokens is basedon the unique identifier.
 13. The computer readable medium of claim 12,wherein the unique identifier includes at least one of a claim number, aline identifier, and a token position on associated with the lineidentifier.
 14. The computer readable medium of claim 11, wherein thecomputer readable medium further comprises instructions that, whenexecuted by the computing system, cause the computing system to: analyzewhitespace associated with the text to form a relationship between atleast two lines of text separated by a line break, wherein the patentspecification is generated based on the relationship of the at least twolines.
 15. The computer readable medium of claim 11, wherein the portionof the NLP tokens comprises a phrase that modifies a root objectassociated with a line of the text.
 16. The computer readable medium ofclaim 11, wherein the computer readable medium further comprisesinstructions that, when executed by the computing system, cause thecomputing system to: generate claim segments for the at least oneindependent claim from the NLP tokens based on an analysis of the NLPtokens.
 17. The computer readable medium of claim 16, wherein thecomputer readable medium further comprises instructions that, whenexecuted by the computing system, cause the computing system to: displayinformation corresponding to the claim segments.
 18. The computerreadable medium of claim 17, wherein a claim segment of the claimsegments is linked to a structure that is associated with the at leastone independent claim.
 19. The computer readable medium of claim 18,wherein the patent specification includes at least one sentenceincluding the structure and text generated based on the claim segment.20. The computer readable medium of claim 11, wherein the computerreadable medium further comprises instructions that, when executed bythe computing system, cause the computing system to: display a userinterface for interacting with the at least one of the text and the NLPtokens, wherein the patent specification is generated based oninteractions within the user interface.